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Seurat is a toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. This guide is to help developers understand how the Seurat
object is structured, how to interact with the object and access data from it, and how to develop new methods for Seurat
objects.
Throughout all Seurat-related documentation and writing, the following styles for distinguishing between Seurat
objects, any associated objects, and the Seurat package will be used. For Seurat
objects, or the object within R, the word 'Seurat' will always be written in monospaced text. When referring to the package Seurat, it will always be written in normal text. Both Seurat and Seurat
will be always capitalized. This style will be used throughout documentation for Seurat as well as any vignettes and tutorials produced by the authors.
The center of all Seurat analyses is the Seurat
object. The Seurat
object is a class allowing for the storage and manipulation of all the single-cell biological data collected on a given set of cells. Previous version of Seurat were designed (almost) exclusively with scRNA-seq data in mind. However, with the development of new technologies allowing for multiple modes of data to be collected from the same set of cells, Seurat 3.0 was redesigned to allow for greater flexibility to work with all these data types in a cohesive framework.
At the top level, the Seurat
object serves as a collection of Assay
and DimReduc
objects, representing expression data and dimensionality reductions of the expression data, respectively. The Assay
objects are designed to hold expression data of a single type, such as RNA-seq gene expression, CITE-seq ADTs, cell hashtags, or imputed gene values. DimReduc
objects represent transformations of the data contained within the Assay
object(s) via various dimensional reduction techniques such as PCA. For class-specific details, including more in depth description of the slots, please see the wiki sections for each class.